Latent Semantic Analysis

The basic idea of latent semantic analysis (LSA) is, that text do have a higher order (=latent semantic) structure which, however, is obscured by word usage (e.g. through the use of synonyms or polysemy). By using conceptual indices that are derived statistically via a truncated singular value decomposition (a two-mode factor analysis) over a given document-term matrix, this variability problem can be overcome.


Reference manual

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0.73.2 by Fridolin Wild, 3 months ago

Browse source code at

Authors: Fridolin Wild

Documentation:   PDF Manual  

Task views: Natural Language Processing

GPL (>= 2) license

Depends on SnowballC

Suggests tm

Imported by DCD, DTWBI, DTWUMI, DiffNet, FSMUMI, IBCF.MTME, IntClust.

Depended on by AurieLSHGaussian, LSAfun, RWBP.

Suggested by quanteda, quanteda.textmodels.

See at CRAN